Handbook of Artificial Intelligence Applications in Energy Systems

Practical Techniques and Case Studies

Häftad, Engelska, 2027

1 926 kr

Kommande

Beskrivning

Handbook of Artificial Intelligence Applications in Energy Systems: Practical Techniques and Case Studies is a practical, step-by-step guidebook for integrating AI into energy systems, from foundational theories to hands-on implementation strategies. This book begins with the foundational principles and history of AI in Energy Systems, including fundamental methods for data preprocessing. A variety of optimization and control strategies are introduced in detail, including advanced methods (Adam, RMSprop, AdaGrad); next, machine learning techniques, libraries, and implementation strategies are broken down in depth. Modeling methods, evaluation metrics, deployment, and interpretability are addressed, before deep learning neural networks from CNNs to GANs, and finally hardware and software requirements for deploying AI in energy systems, including GPU/TPU usage, distributed training, and data storage solution.

Packed with case studies, worked numerical examples, and practical tips for research and implementation in the area, the Handbook of Artificial Intelligence Applications in Energy Systems: Practical Techniques and Case Studies brings the reader quickly up to speed with the practical opportunities of this critical technology in modern energy systems.

Introduces foundational methods for AI use in energy systems, step by step
Works through a host of case studies, practical tests, and numerical examples to bed in knowledge
Includes practical tips for research and industry application, and access to code files, answer keys, and original data

Produktinformation

Utgivningsdatum:2027-03-01
Mått:152 x 229 x undefined mm
Vikt:450 g
Format:Häftad
Språk:Engelska
Antal sidor:400
Förlag:Elsevier Science
ISBN:9780443366888

Utforska kategorier

Energiteknik inom Naturvetenskap och teknik

Mer om författaren

Mir Sayed Shah Danish is currently an Assistant Professor at the Institute of Materials and Systems for Sustainability of Nagoya University, Japan. Dr Danish has a decade of teaching experience, has published over 100 peer-reviewed research articles, and edited/authored several books in Power Electronics and Energy Systems. With an industry background that spans technology and power infrastructure, Dr Danish has been responsible for public-sector power infrastructure projects with budgets totalling over 105-million USD, and was Lead Engineer at Grand Technology Resources (Afghanistan) from 2012-2017.

Innehållsförteckning

1. Introduction to Artificial Intelligence in Energy Systems2. Applications in Energy Systems3. Optimization Algorithms and Strategies in AI for Energy Systems4. Machine Learning Techniques and Frameworks for Energy Systems5. Energy Systems Modeling, Optimization, and Deployment6. Deep Learning Deployment in Energy Systems7. Technical Infrastructure Hardware and Software8. Applied Numerical Example of AI in Energy Systems9. Case Studies: AI Applications in Energy Systems10. Conducting Practical Research in AI and Energy Systems